Health & Demographic Surveillance System Profile: The ...

Health & Demographic Surveillance System Profile

Health & Demographic Surveillance System

Profile: The Ifakara Rural and Urban Health

and Demographic Surveillance System

(Ifakara HDSS)

Eveline Geubbels,1,2,3* Shamte Amri,2,4 Francis Levira,1,3,4

Joanna Schellenberg,5 Honorati Masanja1,2 and Rose Nathan1,2

1Ifakara Health Institute, Mikocheni, Dar es Salaam, Tanzania, 2INDEPTH Network, Kanda, Accra,

Ghana, 3ALPHA Network, London School of Hygiene and Tropical Medicine, London, UK, 4Ifakara

Health Institute, Ifakara Branch, Morogoro Region, Tanzania and 5Department of Disease Control and

Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine,

London, UK

*Corresponding author. Ifakara Health Institute (IHI), Coordination Office, Plot 463, Kiko Avenue, off Old Bagamoyo Road,

Mikocheni P.O Box 78373, Dar es Salaam, Tanzania. E-mail: [email protected]

Accepted 24 March 2015

Abstract

The Ifakara Rural HDSS (125 000 people) was set up in 1996 for a trial of the effectiveness

of social marketing of bed nets on morbidity and mortality of children aged under 5 years,

whereas the Ifakara Urban HDSS (45 000 people) since 2007 has provided demographic

indicators for a typical small urban centre setting. Jointly they form the Ifakara HDSS

(IHDSS), located in the Kilombero valley in south-east Tanzania. Socio-demographic data

are collected twice a year. Current malaria work focuses on phase IV studies for antimal-

arials and on determinants of fine-scale variation of pathogen transmission risk,

to inform malaria elimination strategies. The IHDSS is also used to describe the epidemi-

ology and health system aspects of maternal, neonatal and child health and for interven-

tion trials at individual and health systems levels. More recently, IHDSS researchers have

studied epidemiology, health-seeking and national programme effectiveness for chronic

health problems of adults and older people, including for HIV, tuberculosis and

non-communicable diseases. A focus on understanding vulnerability and designing

methods to enhance equity in access to services are cross-cutting themes in our work.

Unrestricted access to core IHDSS data is in preparation, through INDEPTH iSHARE

[www.indepth-ishare.org] and the IHI data portal [http://data.ihi.or.tz/index.php/catalog/

central].

VC The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association 848

International Journal of Epidemiology, 2015, 848–861

doi: 10.1093/ije/dyv068

Advance Access Publication Date: 15 May 2015

Health & Demographic Surveillance System Profile

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Why was the HDSS set up?

In the 1990s, malaria transmission in the Kilombero valley

was among the highest in subSaharan Africa, with an average

entomological inoculation rate of 300 infectious bites per per-

son per year.1 As a result, malaria was the most important

health problem in the area (Tanner 19912). The Ifakara Rural

HDSS (IR-HDSS) was set up in 1996 as the basis for a field

trial on effectiveness of social marketing of bed nets on mor-

bidity and mortality of children aged under 5 years, the

Kilombero and Ulanga Net project (KINET). A number of

large-scale field intervention trials, epidemiological studies

and impact evaluations for malaria followed. Current malaria

work in humans focuses on Phase IV studies, providing effect-

iveness and safety data for antimalarials. The area of the rural

Ifakara HDSS is also home to one of the largest entomolo-

gical and environmental research programmes in Africa, pro-

viding detailed information on vector ecology and behaviour.

Currently, the environmental malaria research programme in-

vestigates ecological determinants of fine-scale within-village

variation of pathogen transmission risk, which is needed to

prepare for malaria elimination.

Small urban centres are home to around 25% of the

African population and are of social, economic, political

and demographic importance,3 yet few HDSS sites are

located in such settings. The Ifakara Urban HDSS

(IU-HDSS) was set up in 2007 to provide demographic

indicators in a typical small urban centre setting. The

IU-HDSS operates in five areas of Ifakara town, which is

the district capital of Kilombero District.

Both rural and urban HDSS sites are managed by the

Ifakara Health Institute (IHI), which has its coordination

office in Dar es Salaam and runs a further four branches in

the south of Tanzania (Ifakara, Rufiji, Bagamoyo,

Mtwara). At over 50 years, Ifakara is the oldest branch

and forms part of a unique cluster of organizations provid-

ing health services, training and research. As part of the

Ifakara branch, the Ifakara HDSS (IHDSS) is the central

platform for research in six themes along the research to

policy and practice pipeline. Within these themes, projects

are centred on a particular health problem (Figure 1).

What does it cover?

In the late 1990s, maternal, neonatal and child health

(MNCH) became a second focus of the IR-HDSS, first by

describing the epidemiology of and barriers to access to care

and quality of care. These were followed by intervention tri-

als at individual and health systems levels. More recently, IHI

researchers have studied chronic health problems of adults

and older people as a third focus in the IHDSS. These include

HIV, tuberculosis and non-communicable diseases (NCDs).

Last, a programme on neglected tropical diseases was added,

notably on the epidemiology and control of rabies and Rift

Valley Fever. In addition, the core Ifakara HDSS generates

patterns and trends of fertility and mortality, as well as cause-

specific mortality for all age groups, by socioeconomic status.

Table 1 gives a more detailed overview of the aims of the cur-

rent and future studies, addressed in our four programmes.

Population-based survey data will be linked to detailed clin-

ical data from the KIULARCO HIV cohort at the Chronic

Disease Clinic Ifakara4 to facilitate studies on linkage into

care and on retention in care and treatment.

Where is the HDSS area?

The IHDSS is located approximately 450 km by road from

Tanzania’s commercial capital, Dar es Salaam. The HDSS

covers an area of 2400 km2 across two districts,

Kilombero and Ulanga in Morogoro Region, and lies

between latitudes 8�00’S and 8�35’S and longitude

35�58’E to 36�48’E at the altitude of 270–1000 m above

sea level. The mean household size is 4.2 and people usu-

ally live in a compound with one or two houses. The HDSS

area encompasses nine dispensaries, one health centre and

one referral hospital (Figure 2).

Ifakara Rural DSS

Households in the IR-HDSS are scattered in the Kilombero

Valley, wedged in between the Udzungwa Mountains trop-

ical rainforest, the grassland-covered Mahenge Mountains

and the woodland Selous Game Reserve. The valley forms

a seasonal flood plain of up to 52 km wide at high water,

Key Messages

• IHI’s multidisciplinary skills set, good research infrastructure, coupled with the unique position of IHDSS in a cluster

of research, health service delivery and health training organizations at district level allow for research along the en-

tire pipeline of intervention development to impact evaluation.

• Our experience in the malaria and child health fields demonstrates capacity to translate knowledge into action and to

influence policy at district, national and international levels, and has brought notable health improvements to the

HDSS area and beyond.

• The Ifakara urban HDSS is among the few HDSS sites located in small urban settings, which are estimated to be

home to 25% of Africa’s population.

International Journal of Epidemiology, 2015, Vol. 44, No. 3 849

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and has an annual rainfall of 1200–1800 mm and tempera-

tures that range between 25�C and 32�C. During the rainy

season from November to May, households in some

villages are not accessible by motor vehicle. The main

economic activity is subsistence farming, especially of rice.

Small-scale fishing, hunting and pastoral livestock rearing

are also practised. The main vector species are Anopheles

spp., Culex spp, Aedes spp. and Mansonia spp.5

Figure 1. (A) Position of Ifakara HDSS in the Ifakara research, training and service delivery structure; (B) Research pipeline of the Ifakara HDSS six

research thematic groups and their topic areas.

850 International Journal of Epidemiology, 2015, Vol. 44, No. 3

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Table 1. Current and future programme aims of studies based at Ifakara HDSS

Programme aims Study type

Malaria

Current

Assess effectiveness and safety of newly introduced antimalarials Phase IV observational cohort, surveillance

Develop novel vector control interventions, including spatial repellents,

odour-baited devices, mosquito filial infanticides and insect growth

regulators, botanical and biological control agents

Entomological cohort studies

Determine ecological determinants of variation in pathogen transmission

risk

Entomological field studies

Future

Test the malaria transmission impact of the above novel vector control

interventions

Field trials

Maternal neonatal and child health

Current

Describe patterns of maternal, neonatal and infant morbidity and

mortality and their structural associates

Demographic studies

Understand individual and health systems delays in delivery care Implementation studies

Test efficacy of neonatal vitamin A supplementation on neonatal

survival

Field trial

Test efficacy on maternal and child mortality of deploying paid

community health workers for providing preventive, promotionaL

and curative antenatal, new-born, child, and reproductive health care

Field trial

Future

Assess the determinants of early child development Population-based cohort study

Evaluation the impact of community-based family planning

service delivery

Population-based cohort study and implementation

science studies

Chronic disease

Current

Describe prevalence and incidence, comorbidity and mortality for

HIV and selected NCDs

Population-based cohort study

Understand impact of biological, lifestyle-related and social determinants

of chronic disease and healthy ageing

Population-based cohort and cross-sectional studies,

sociological studies

Assess changes in sexual behaviour, attitudes and risk perception Epidemiological and sociological studies

Explore community perceptions around emerging chronic diseases such

as diabetes and their impact on health seeking behaviourS

Sociological studies

Assess constraints and opportunities to adapt the health system architecture

to deal with chronic illness

Implementation science studies

Identify factors affecting antiretroviral treatment (ART) adherence and

occurrence of drug resistance

Clinical cohort study

Evaluate the impact of the ART programme Population-based cohort study and implementation

studies

Future

Dynamics of couple communication in relation to sexual risk-taking and

VCT testing

Sociological study

Health systems intervention for diabetes Field trial

Female cancer risk factors, burden, suffering and pathways to care Population-based cohort study

Health systems intervention studies for female cancers Implementation science studies

Neglected tropical diseases

Current

Epidemiology of inter-epidemic transmission of Rift Valley Fever Population- and livestock-based cross-sectional studies

Burden of rabies and impact on communities Surveillance and implementation science studies

Future

Understanding transmission dynamics between epidemics Entomological, facility- and community-based surveillance,

mathematical modelling

VCT, Voluntary Counseling and Testing.


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Ifakara Urban HDSS

In contrast, households in the IU-HDSS are mainly concen-

trated in the bustling district capital of Ifakara town, with

a gradual transition to lower-density settlements towards

the edges of the Demographic Surveillance Area (DSA).

Economic activity is centred on agricultural trade, farming

and provision of higher education, especially in the medical

fields. As a consequence, Ifakara town is undergoing rapid

changes in its built environment and social structure, with

people from more than 70 ethnic groups currently resident

in the IU-HDSS, 60% of whom are in-migrants to the area.

The construction of a bridge over the Kilombero River and

a major transit road is expected to contribute to further

changes in the near future.

Who is covered by the HDSS and how oftenhave they been followed up?

The IR-HDSS covers 25 villages in Ulanga and Kilombero

districts, comprising 126 836 people in 30 855 households,

whereas the IU-HDSS consists of five areas of Ifakara

town, with 44 992 people in 10 712 households (as at 31

December 2012). The population structure of IR-HDSS

(Figure 3A) is typical of a rural African population, with

Figure 2a. Location of Ifakara HDSS in Kilombero and Ulanga districts in Tanzania.


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46% of participants under 15 years old. In IU-HDSS only

38% of inhabitants are younger than 15, and 7% are 60

years or older (Figure 3B). Both HDSS sites show evidence

of net out-migration for young men, mainly for the pur-

pose of finding employment in more urbanized areas to

support themselves and their extended families.

The main ethnic groups in the valley are traditionally

farmers, with smaller proportions of pastoralists who

migrated into the area from the north and centre of

Tanzania. Over three-quarters of participants have had at

least some schooling, though only 23% have gone beyond

primary school.

Figure 2b. Map of Ifakara Urban and Rural DSS showing villages and town areas under surveillance, the Kilombero floodplain, primary and secon-

dary roads and location of health facilities.

Figure 3. Population pyramid of (A) Ifakara Rural HDSS; (B) Ifakara Urban HDSS, 2012.


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Table 2. Additional variables collected in the IHDSS

Variable Location and

population

Period Modality R¼ HDSS

rounds

S ¼ special survey

Update frequency

Environmental risk factors

Latitude, longitude and altitude Households in both

HDSS

2006 – on-going R 2 per year

House building materials Households in both

HDSS

2007 (IU) - on-going R 1 per year

2000 (IR) - on-going

Malaria risk factors

Bed net ownership Households in both

HDSS



Bed net use Households in both

HDSS



MNCH risk factors

Pregnancy outcome Newborns in both

HDSS

2007 (IU) - on-going R 3 per year till 7/13

1997 (IR) - on-going 2 per year from 7/13

Birthweight Newborns in both

HDSS

2010 - on-going R 3 per year till 7/13

2 per year from 7/13

Family planning use Women in both HDSS 2011 – on-going R 3 per year till 7/13


Family planning intentions Women in both HDSS 2011 – on-going R 3 per year till 7/13


Child vaccination status U5 in both HDSS 2000- on-going R 3 per year till 7/13


Pregnant women’s anthropometrics Pregnant women in

both HDSS

2012 – 2013 S 3 per year till 7/13


Pregnant women’s nutritional intake Pregnant women in

both HDSS

2012 – 2013 S 3 per year till 7/13


HIV and STI risk factors

Sexual behaviour Adults 15þ in part of

IU-HDSS

2012/3 and 2014/5 S Once every 2 years

HIV and STI KAP Adults 15þ in part of

IU-HDSS


NCD risk factors

Height, weight, WC, HC Adults 15þ in part of

IU-HDSS


Smoking Adults 15þ in part of

IU-HDSS


Alcohol use Adults 15þ in part of

IU-HDSS


Diet Adults 15þ in part of

IU-HDSS


Physical exercise Adults 15þ in part of

IU-HDSS


Family history of NCD Adults 15þ in part of

IU-HDSS


Sleep patterns Adults 15þ in part of

IU-HDSS

2014/5 S Once every 2 years

(Continued)


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Despite the variety of ethnic groups, Swahili is the main

language of communication in both parts of the HDSS,

whereas English is also spoken by professionals living in

the urban HDSS.

For the IR-HDSS the baseline census happened between

September and December 1996, and for the IU-HDSS the

census was done between January and April 2007. All indi-

viduals who were intending to be resident in the DSA for

at least 4 months were eligible for inclusion. Verbal

consent to participate in the census was sought from the

head of every family. After the census, the study popula-

tion was visited three times a year in January–April,

May–August and September–December, to document

demographic events in each household including

in-migration, out-migration, births and deaths. From mid

2013 onward, both HDSS sites switched to two data

collection rounds per annum, which happen in

July–December and January–June.

Table 2. Continued

Variable Location and

population

Period Modality R¼ HDSS

rounds

S ¼ special survey

Update frequency

Social determinants

Occupation Adults in both HDSS 2000 - on-going R Once per year

Education All 6þ in both HDSS 2000 - on-going R Once per year

Household wealth Households in both

HDSS

2000 - on-going R Once per year

Gender attitudes Adults 15þ in part of

IU-HDSS


Social group membership Adults 15þ in part of

IU-HDSS


Social capital Adults 15þ in part of

IU-HDSS

2014/5 S Once every 2 years

Religion and ethnic group Adults 15þ in part of

IU-HDSS


Health seeking

HIV testing history Adults 15þ in part of

IU-HDSS


NCD testing history Adults 15þ in part of

IU-HDSS


Mother’s ANC attendance Newborns in both

HDSS

2000 - on-going R 3x per year till 7/13

2x per year from 7/13

Place and mode of delivery Newborns in both

HDSS



Skilled assistance at delivery Newborns in both

HDSS



Health outcomes

Height/length, weight and MUAC U5 in both HDSS 2010 S Once

History of fever, diarrhoea, respiratory

problems in past 2 weeks

U5 in both HDSS 2011 – on-going R 3 per year till 7/13


Blood pressure Adults 15þ in part of

IU-HDSS


Blood glucose Adults 15þ in part of

IU-HDSS


HIV status Adults 15þ in part of

IU-HDSS


MNCH, maternal, neonatal and child health; STI, sexually transmitted infection; KAP, knowledge, attitudes and practices; WC, waist circumference; HC, hip

circumference; MUAC, mid upper arm circumference; ANC, antenatal clinic; 15þ, aged 15 years and over (¼ ‘adult’); 6þ, aged 6 years and over; U5, aged under

5 years.


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What has been measured and how are HDSSdatabases constructed?

Interviewers collect information on core HDSS data that

identify households and individuals, spousal relationships,

maternal and paternal parenthood and observe pregnancy,

birth, death and migration events, using standard

INDEPTH definitions and procedures.6

Physicians code cause of death (COD) as based on

standardized INDEPTH Network verbal autopsy (VA)

forms version 2007, using the 10th revision of the

International Classification of Diseases. A wide range of

other information on household characteristics, disease-

specific risk factors, social determinants, health-seeking

behaviours and health outcomes has been collected in all

or parts of the DSS population, be it as part of routine

HDSS rounds or in special surveys (Table 2). In the

IR-HDSS, VA interviews only started in 2000.

We actively engage the community through key inform-

ants and ‘balozi’: local leaders of typically between 10 and

50 houses. Findings are fed back to the community

through these channels and in newsletters. Specific com-

munity sensitization events are held at the time of introduc-

ing new studies.

As from 1 July 2013, data collection and storage in the

IHDSS have been using the open-source OpenHDS system.7

Data are collected through tablets incorporating real-time

validity checks and uploaded to the database server daily,

which improves quality, timeliness and efficiency of data

collection. Though part of the HDSS is very remote, all field

interviewers are able to charge their tablets and upload

data, be it sometimes in creative ways (Figure 4).

Key findings and publications

The decline in under-five mortality in IR-HDSS was 51%

between 2000 and 2012, but was almost negligible in IU-

HDSS. Adult mortality declines were also higher in IR-

HDSS (19%) than IU-HDSS (14%). Neonatal mortality

has remained relatively stable over time in both sites.8

These changes have resulted in mortality rates that are

now higher in IU-HDSS than IR-HDSS and a life expect-

ancy at birth that is higher for the rural population than

for inhabitants of Ifakara town (Table 3). With a sustained

total fertility rate (TFR) of 4.4, no clear evidence of demo-

graphic transition is evident yet in IR-HDSS, but a much

lower TFR of 3.0 is observed in IU-HDSS.

Malaria

It is plausible that the dramatic decrease in child mortality

nationally between 1999 and 2010 can be attributed in

large part to a series of malaria prevention and health

systems interventions developed and scaled up in the past

one and a half-decade.9 IHI researchers and collaborators

in the KINET project showed that locally contextualized

social marketing of insecticide-treated bed nets was associ-

ated with a 27% increase in survival in children aged 1

month to 4 years.10 This was achieved because the pro-

gramme dramatically increased net ownership and

improved equity of ownership.11

In other studies related to the KINET project, we

showed that treated nets had a protective efficacy of 62%

and 63% for parasitaemia and anaemia, respectively,

among children under 2 years of age.12 Among pregnant

women, protective efficacy was 23% for parasitaemia and

38% for severe anaemia, respectively.13 We demonstrated

that discount vouchers are a feasible approach to target

subsidies for bed nets.14 The KINET studies informed the

design of the Tanzania National Voucher Scheme, the

scale-up and effect of which IHI and partners are now

monitoring and evaluating.15

Ifakara HDSS has also been used for evaluating new

diagnostics, treatment regimens and delivery strategies as

they are rolled out nationally. Between 1997 and 2009,

child mortality decreased by 42.5% in the Ifakara rural

DSS. The increase in mosquito net coverage, the switch to

sulfadoxine-pyrimethamine (SP) as first line treatment, the

introduction of Integrated Management of Childhood

Illnesses (IMCI) and the start of a social marketing cam-

paign and drug distribution through Accredited Drug

Dispensing Outlets in private pharmacies16 all contributed

to this decline.17 Despite higher rates of adequate clinical

and parasitological response under artemisinin combination

therapy (ACT) compared with SP,18 the effect of introduc-

tion of ACT on the child mortality trend was minimal.18

Possibly this is because over 50% of patients do not access

an authorized ACT provider promptly19 and because of

challenges in health system design and governance.20,21

Over-prescription of ACT exists alongside challenges in

timely access. Masanja et al reported though, that the intro-

duction of malaria rapid diagnostic tests for parasitological

confirmation reduced over-prescription of ACT.22

Alongside impact on morbidity and mortality, IHI

researchers have documented the impact of various malaria

interventions on vector behaviour and malaria transmission.

The introduction of ACT in the Tanzanian health system

only modestly decreased prevalence of asexual parasit-

aemia23 and did not influence the overall infectiousness of

the human population.24 High usage of insecticide-treated

bed nets (ITNs) leads to greatly reduced indoor transmission

and a relatively larger proportion of residual transmission

happening outdoors.25 Both indicate that additional control

tools are needed to eliminate malaria.


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Maternal, neonatal and child health

Tanzania’s maternal mortality ratio and neonatal mortality

rate remain high.26 Women with mistimed or unwanted

pregnancies initiate antenatal care later, thereby denying

themselves access to early detection and management of

potential pregnancy complications.27 We showed that in

the period 2005–07, i.e. before quality improvement

programmes started, delivery in health facilities was not

associated with better neonatal survival.28 Met need for

comprehensive emergency obstetric care (CEmOC) is

unacceptably low, especially in remote areas, against a

background of severe shortage of physicians. IHI’s

EMPOWER project showed that non-physician health

workers can effectively deliver CEmOC and anaesthesia

in remote health centres, when trained by a competence-

based in-service course.29 EMPOWER also demonstrated

that distribution of misoprostol (a uterotonic drug)

to expectant mothers for use after home delivery is a

Figure 4. HDSS field interviewer climbing up a palm tree to access network to upload data.

Table 3. Demographic characteristics of the Ifakara HDSS, 2012

Ifakara Rural HDSS Ifakara Urban HDSS

General Fertility Rate (GFR) 142.1 95.1

Total Fertility Rate (TFR) 4.4 3.0

Neonatal mortality rate per 1000 live births 22.7a 34.0

Infant mortality rate per 1000 live births 43.4a 63.4

Child mortality rate per 1000 live births 24.7a 27.0

Under-five mortality rate per 1000 live births 66.6a 88.7

Adult mortality rate (15–59 years) 243.0 260.5

Life expectancy, males 63.4 60.1

Life expectancy, females 69.0 65.4

GFR: number of live births per 1000 person-years of women of reproductive age (15–49); TFR, projected total number of births by end of a woman’s childbear-

ing period at current age-specific fertility rates.a2011 estimate.


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feasible, safe, effective and acceptable way to protect

against life-threatening post-partum haemorrhage.30

Early studies of child mortality demonstrated that most

of the children had sought treatment at a health facility

during their fatal illness episode.31 This suggested that

interventions to improve case management, such as IMCI,

might be beneficial. In subsequent studies in collaboration

with the Rufiji HDSS, we showed that the introduction of

IMCI led to improvement in child health that was good

value for money and did not occur at the expense of

equity.32,33 IMCI was implemented as national policy in

2004 and IHI researchers and partners continue to investi-

gate the barriers to scale-up34 and best support strategies

for implementation.35

Chronic diseases

In Tanzania, as in many other African countries, NCDs are

increasing as a result of demographic and epidemiological

transitions. We documented that whereas HIV and malaria

were the two most common causes of death among adults,

NCD deaths increased from 16% to 24% of all adult

deaths in the IR-HDSS between 2003 and 2007. Contrary

to popular belief, adults with lower education had higher

hazard of dying from an NCD. Cerebrovascular disease

and epilepsy were among the more common NCD-related

causes of deaths.36 The SEEDS study showed that

IR-HDSS had the highest prevalence of active convulsive

epilepsy among five sites in subSaharan Africa (SSA) at

14.8 [95% confidence interval (CI): 13.8–15.4] per 1000

population screened. Population attributable fractions

indicated that interruption of transmission of parasitic

disease and improved antenatal and perinatal care would

prevent the majority of adult-onset epilepsy and half of

childhood-onset disease.37

The Innovative Care for Chronic Conditions framework

of the World Health Organization (WHO)38 calls for a pre-

pared, motivated and informed triad of patients with fam-

ily members, community partners and health care teams

who interact in an environment supported by a health sys-

tem linked to the community in a positive policy environ-

ment. For infectious chronic diseases, a few studies in the

IHDSS addressed elements of this framework. Community-

based directly observed treatment (DOT) for tuberculosis

was shown to be acceptable and to produce patient out-

comes as good facility-based DOT.39 Conditional cash

transfers used to incentivize safer sexual practices may be

an appropriate tool in prevention of HIV and other sexu-

ally transmitted infections.40 The current public policy,

health system and community actions against NCDs are

still far from adequate, though, to prevent and control the

rapidly rising burden of NCDs in our population.41

As is the case for many communicable diseases, demo-

graphic disparities exist in burden of disease and suffering.

In the 2007, the WHO-INDEPTH-SAGE study on health

status and quality of life among people of 50 years and

over, men, married people and the younger age categories

in IR-HDSS reported better quality of life and health status

than did women, single people and older age groups.42

Lower reported health status was most strongly associated

with the domains of pain and reduced mobility, whereas

the domains of interpersonal relations and level of self-care

affected health status the least.43 This is possibly a reflec-

tion of the fact that the vast majority of older people in IR-

HDSS live in extended families, and illustrates that social

capital alone, without sufficient access to diagnosis and

care for chronic health problems, is not sufficient to ensure

a healthy old age.

Neglected tropical diseases

Rift Valley Fever (RVF) is a zoonotic disease formerly

believed to occur mainly in epidemics triggered by unusu-

ally high rainfall. Recently, we demonstrated existence of

constant inter-epidemic exposure to RVF virus in both ani-

mals44 and humans45 in the Kilombero Valley. Research

on rabies in the IHDSS demonstrated that whereas most

patients live below the poverty line, an average patient

would need to spend more than US $100 to complete rec-

ommended post-exposure prophylaxis. This high cost,

coupled with stock-outs and diagnostic delays, led to

increased risk of death.46 A national mass dog vaccination

campaign against rabies had low coverage in the study

area and operational research suggested that mass inter-

ventions for neglected diseases need to better involve the

community and take into account project organization and

delivery capacity.47

All publications from the Ifakara HDSS and the wider

Tanzanian health research community can be accessed

through [http://digitallibrary.ihi.or.tz].

Future analysis plans

In the short term we will do a comparative analysis of

patterns and drivers of fertility trends in the past decade,

with the Rufiji HDSS. We are developing a mathematical

model for projection of mortality due to febrile illness. We

also plan to quantify and qualify the effects of NCDs on

fertility and birth outcomes. We will characterize

HIV-NCD comorbidity patterns and mortality impacts and

will analyse health-seeking trajectories for fatal chronic

disease. Risk factor analysis will focus on the social deter-

minants of sexual and lifestyle behaviour and consequent

health outcomes. We welcome collaborations on these and

other not yet identified secondary analyses.


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http://digitallibrary.ihi.or.tz

Strengths and weaknesses

Strengths

In the past all human settlements used to be classified as

either ‘rural’ or ‘urban’. Human development specialists

argued that this classification system does not help us

understand the new types of urbanization that are develop-

ing in low- and middle-income countries (LMIC), nor the

diversity of these settlements across the continuum

between rural to urban and the functional connections

between them.48 The Ifakara HDSS provides a study plat-

form across the rural to small-urban town continuum.

Furthermore, the availability of the Rufiji and Ifakara

HDSS under one institutional roof continues to provide a

large enough platform to allow testing of novel commu-

nity-based or facility-based interventions in a cluster-

randomized comparative design.

With the introduction of OpenHDS, high quality core

demographic data are now available in a much timelier man-

ner and at reduced cost. The electronic data collection also

allows more flexibility to add on project-specific questions

to HDSS rounds. Another key strength of IHI is its large and

multidisciplinary skills set, with demographers, epidemiolo-

gists, software developers, clinicians, laboratory scientists,

entomologists, health economists, behavioural scientists and

policy analysts. The Ifakara HDSS site has good infrastruc-

tural facilities (screen houses, well equipped laboratory) and

enjoys close working relations with the referral hospital St.

Francis and the Tanzanian Training Center for International

Health.29 Lastly, as our key findings show, we have proven

experience in knowledge translation and policy influence at

district, national and international levels.

Weaknesses

Because of the manual and centralized coding, we still have

a turn-around time of about 1 year between a death occur-

ring and the COD being assigned. An indeterminate COD

is often assigned in neonatal and child deaths occurring

outside the hospital, especially in less educated families.49

We are currently preparing electronic capture and auto-

mated coding of VA data, which should bring down this

time lag to a few months and increase the percentage

coded. High migration in urban DSS brings challenges to

capture the mobile population. Lastly, delayed enrolment

of new households settling in the area has occurred at least

twice since the start of the HDSS.

Data sharing and collaboration

Many of the current programmes in Ifakara HDSS are the

fruit of (inter)national collaborations, with colleagues at

other INDEPTH sites, the National Institute for Medical

Research, Muhimbili University of Health and Allied

Sciences, Sokoine University of Agriculture, Swiss Tropical

Public Health institute, London School of Hygiene and

Tropical Medicine, Columbia University, Harvard

University, Royal Tropical Institute, University of

Groningen, Durham University and Liverpool School of

Tropical Medicine.

We welcome applications to use IHDSS data for collab-

orative analysis, by submitting a proposal to the impact

evaluation thematic group lead, Dr Eveline Geubbels, at

[[email protected]]. Unrestricted data access is in prepar-

ation for the core IHDSS data, through the INDEPTH

iSHARE data repository [www.indepth-ishare.org] and the

IHI data portal [http://data.ihi.or.tz/index.php/catalog/

central].

Funding

Many funders have supported the IHDSS over the years, through

funding of core activities or project contributions. These include the

Tanzania Ministry of Health and Social Welfare, Swiss Agency for

Development Corporation, World Health Organization, Global

Fund for AIDS, TB and Malaria, World Bank, International

Development Research Center, Netherlands Organization for

International Cooperation in Higher Learning, UK Department

for International Development, Norad, United States Agency for

International Development, President’s Malaria Initiative, Doris

Duke Foundation, Bill & Melinda Gates Foundation, COMIC

Relief UK, Rockefeller Foundation, Novartis Foundation, the

European Union and the INDEPTH Network.

AcknowledgementsThanks go first and foremost to HDSS participants, Council Health

Management Team members, ward leaders, village leaders and

balozi in Kilombero and Ulanga and to colleagues Christosom

Mahutanga, Jensen Charles, Jumanne Kisweka, Jackson Francis,

Mathew Manyangala, Robert Sumaye, Tumaini Kilimba, Advocatus

Kakorozya, Isaac Lyatuu, Aurelio DiPasquale, Malick Kante and all

other staff who have contributed to the HDSS platform in the past

two decades. We also thank Fredros Okumu, Paul Muneja and

Godfrey Mbaruku for their contributions to this paper. Last, we are

grateful to the INDEPTH international network of HDSS sites

[http://www.indepthnetwork.org] and the ALPHA network for

analysis of longitudinal, population-based HIV/AIDS data in Africa

in 2010 [http://www.lshtm.ac.uk/eph/psd/alpha] for their capacity-

building efforts.

Conflict of interest: None declared.

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